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JSM 2012 Online Program

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Activity Details

CE_21C Tue, 7/31/2012, 8:30 AM - 5:00 PM HQ-Indigo A
An Introduction to Statistical Learning — Continuing Education Course
ASA , Section on Statistical Learning and Data Mining
Instructor(s): Gareth James, University of Southern California, Yufeng Liu, The University of North Carolina at Chapel Hill
This one-day seminar will be a practical introduction to and an overview of statistical learning methods. The course aims to go far beyond classical statistical methods such as linear regression. As computing power has increased over the last 20 years many new, highly computational, regression, or "Statistical Learning", methods have been developed. In particular the last decade has seen a significant expansion of the number of possible approaches. This course aims to provide an applied overview to such modern methods as Cross-validation, Lasso, Generalized Additive Models, Decision Trees and Support Vector Machines as well as more classical approaches such as Linear Discriminant Analysis, Quadratic Discriminant Analysis, Nearest Neighbors and Ridge Regression. Participants should be familiar with linear regression.

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